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Matthijs Brouns

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titleconferencedate
10x smaller docker containers for Data SciencePyData Eindhoven 20202020-10-07
Starts from a 1.7 GB baseline and actually reduces a PyData image with Matplotlib Scipy Numpy and Scikit-learn down to ~188 MB using concrete steps: use…
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Pipelines for Fairness: A Convexing UsecasePyData Eindhoven 20192019-11-16
Pipeline approach presents concrete fixes and measured tradeoffs: a modified Gram-Schmidt transformer removes linear dependence on protected columns inside a…
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